Which statistical measure would be more affected by extreme values?

The range is the correct choice because it is defined as the difference between the maximum and minimum values in a dataset. As a result, the presence of extreme values, or outliers, can significantly alter the range. For example, if you have a dataset with mostly small numbers and suddenly include a very large number, the range will increase substantially, reflecting the influence of this extreme value.

In contrast, the median, which is the middle value when the data is ordered, is less affected by outliers. It remains stable even when extreme values are present in the dataset. The mode represents the most frequently occurring value in the dataset, and while it can be influenced by extremes if they occur frequently, it does not shift simply due to the presence of a single outlier or extreme value.

The interquartile range (IQR), which measures the middle 50% of the data (the difference between the first quartile and the third quartile), also remains unaffected by extreme values because it focuses solely on the central portion of the dataset. Hence, the range is the most sensitive to extremes, making it the appropriate choice in this context.